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Jeremy Grantham joins Excess Returns to discuss The Making of a Permabear, mean reversion, market bubbles, AI, the Magnificent 7, and the long-term lessons investors can take from his career at GMO. We cover why he rejects the simple “permabear” label, how he thinks about valuation and bubbles, why AI may be both transformative and dangerous for investors, and why long-term thinking is so hard but so essential.The Making of a Permabear: The Perils of Long-term Investing in a Short-term Worldhttps://groveatlantic.com/book/the-making-of-a-permabear/GMOhttps://www.gmo.com/americas/Grantham Foundationhttps://granthamfoundation.org/Topics covered:Why Jeremy Grantham thinks the “permabear” label misses the pointThe difference between being generally bearish and making a true “abandon ship” callMean reversion, valuation cycles, and why history still matters for investorsWhy monopoly power helped reshape U.S. profit margins and market concentrationHow AI could turn today’s monopoly winners into brutal competitorsWhy new technology often becomes a cost of doing business rather than a permanent profit boostHow Grantham defines bubbles using two-sigma market eventsLessons from Japan, the dot-com bubble, the housing bubble, and the 2021 speculative peakWhy institutional investors struggle to stick with value strategies during bubblesThe role of purpose, climate risk, toxicity, and long-term thinking in Grantham’s later careerThe one lesson Grantham would teach ordinary investors about pessimism, realism, and time horizonsTimestamps:00:00 Jeremy Grantham on unpleasant news and long-term investing04:18 Reinvesting when terrified in 200908:43 Why Grantham told investors to abandon ship in 200810:28 Mean reversion and why history matters14:00 Monopoly power, the Mag 7, and rising market concentration17:14 Why AI is important but impossible to forecast20:21 AI as a cost of doing business21:24 From monopoly profits to brutal AI competition24:05 How investors should think about valuation mean reversion27:00 Why high returns on capital should eventually attract competition29:47 How Grantham defines a market bubble33:00 Japan’s extreme bubble and GMO’s zero weight decision34:19 The dot-com bubble and the pain of being early38:00 Grantham’s bubble warning signal in 202141:35 Whether today’s market is showing classic bubble behavior43:00 QuantumScape, meme stocks, and speculative excess46:35 How ChatGPT interrupted the 2022 bear market49:12 Investor behavior and the cost of underperforming in a bubble55:00 Purpose, philanthropy, climate risk, and useful work01:01:03 The one lesson Grantham would teach average investors

Marc Rubinstein joins Excess Returns to explain what private credit, bank earnings, insurance balance sheets, fintech growth, and arbitrage firms reveal about the modern financial system. The conversation covers why private credit risks may not be systemic in the traditional banking-crisis sense, but still matter for investors because of redemption gates, hidden leverage, opaque structures, incentive conflicts, and correlations that can spike when markets are under stress.Marc Rubinstein on Xhttps://x.com/MarcRubyNet Interesthttps://www.netinterest.co/In this episode, we discuss:Why the Fed says private credit redemption risks are limited and manageableWhat Blue Owl’s redemption gates reveal about private credit liquidityHow post-2008 bank regulation pushed risk into private credit, hedge funds, trading firms, and exchangesWhy banks and private credit firms are both competitors and collaboratorsThe “layer cake” of leverage connecting banks, private credit, and borrowersHow HSBC’s loss tied to Atlas and MFS highlights hidden credit risksWhy insurance companies have become increasingly tied to private creditWhy rapid growth can be dangerous in financial businessesWhat bank earnings show about the gap between weak consumer confidence and resilient spendingWhy post-mortem reports from SVB, Credit Suisse, and other failures reveal what investors could not see in real timeHow Revolut became one of the most interesting fintech stories in global bankingWhy Marc calls this a potential golden age of arbitrageWhat Jane Street, public BDC discounts, private asset valuations, and geopolitical fragmentation tell us about market structureWhy investors may still be too anchored to the 2008 banking playbookWhere Marc sees risk and opportunity in financials, banks, Europe, and non-bank financial institutionsTimestamps:00:00 Private credit, hidden risks, and correlation spikes05:03 Why Blue Owl became a private credit warning sign10:20 How private credit grew after the 2008 financial crisis15:30 Banks and private credit as financial “frenemies”19:44 HSBC, Atlas, MFS, and the layer cake of leverage24:11 Apollo, Athene, insurance assets, and private credit incentives29:20 Why higher rates have not broken more of the financial system33:40 Bank earnings, consumer confidence, and resilient spending37:20 Why “I don’t know” can be a powerful signal from bank CEOs41:46 Revolut and the ambition to build a truly global bank47:38 Why growth can be dangerous in finance52:19 Private assets, public BDC discounts, and arbitrage opportunities56:34 What investors misunderstand about banks today59:31 How Marc would think about financials as a long-short investor

First Principles with Andy Constan launches with a deep dive into market bubbles, AI, semiconductor stocks, and the financial conditions that can turn powerful technological change into a dangerous investment regime. Andy explains how bubbles form, why they are almost impossible to time, how today’s AI boom compares to past episodes like 1987, the dot-com bubble, housing, and the bond bubble, and what investors should watch as expectations, financing, and FOMO build.Andy Constan on Xhttps://x.com/dampedspringDamped Spring Advisorshttps://dampedspring.com/Topics covered:Why bubbles are easy to identify in hindsight but nearly impossible to define in real timeThe difference between an expensive market and a true bubble regimeHow new technologies, easy money, regulation, and exogenous shocks can create bubble conditionsWhy AI may rhyme with the internet boom without being an exact repeatThe role of ChatGPT, Microsoft’s OpenAI investment, and semiconductor earnings expectationsWhat the 1987 crash, Japan, housing, bonds, and dot-com bubble can teach investors todayWhy human nature, FOMO, and “keeping up with the Joneses” make bubbles so powerfulHow the late-1990s Fed response to Long-Term Capital Management helped fuel the final phase of the tech bubbleWhy tech’s current size in the economy and market may limit how far the AI boom can growHow AI capex, hyperscaler spending, buybacks, debt issuance, and IPO supply could determine what happens nextTimestamps:00:00 Intro and the challenge of identifying bubbles04:32 Expensive markets vs true bubble regimes09:57 The five bubble episodes Andy compares to today14:35 Root conditions, escalation events, and the peaking phase19:20 Why the 1987 crash may also have been a bubble24:25 The late-1990s setup and the Netscape Navigator moment28:00 Crisis analogs, easy financial conditions, and today’s AI parallels32:20 Long-Term Capital Management and rocket fuel for the tech bubble36:11 Why tech’s market share matters more today than in the 1990s43:18 Policy mistakes, subsidies, and how governments feed bubbles47:42 Semiconductor earnings expectations and valuation risk53:45 The AI capex chain and where the money has to come from58:42 IPOs, corporate debt, and the financing risk behind the AI boom01:02:27 What investors should do differently in a bubble regime

Edward Chancellor joins Kai Wu on the latest episode of the Intangible Economy to discuss what financial history and capital cycle theory can teach investors about today’s AI boom. They explore why transformative technologies can still produce terrible investor returns, how overinvestment develops, where anti-bubbles may be forming, and what past episodes like the railway mania, the dot-com bubble, China’s investment boom and the post-2008 interest rate regime suggest about the risks and opportunities today.Subscribe on SpotifySubscribe on AppleTopics covered:How capital cycle theory applies to the AI data center boomWhy railway mania, autos, aircraft and the dot-com bubble offer lessons for todayWhy markets often fund major technology transitions but fail to identify the winnersThe prisoner’s dilemma driving hyperscaler AI spendingWhether AI demand can justify the supply being builtHow GPU depreciation and AI capital spending may affect reported earningsWhy hallucinations and reliability may limit the total addressable market for large language modelsThe case for looking at AI anti-bubbles instead of shorting the bubble directlyWhy China shows that strong GDP growth does not guarantee strong shareholder returnsHow intangible capital, SaaS valuations and human capital fit into capital cycle analysisWhether bubbles can be good for society while still being bad for investorsWhy the long-term interest rate cycle may have changedThe role of gold in a world of expensive stocks, rising debt and vulnerable bondsTimestamps:00:00 Edward Chancellor on capital cycles, bubbles and AI04:42 Why the railway mania became a classic overinvestment cycle09:00 Why markets fund technology booms but often miss the winners13:19 The prisoner’s dilemma behind AI spending17:30 Will AI demand justify the supply being built20:00 How capital spending can inflate profits before the bust25:08 The AI Hindenburg moment and the limits of large language models30:55 Why AI hype may exceed the proven technology35:55 Why the anti-bubble may matter more than shorting AI40:00 The energy transition bubble and the opportunity in overlooked assets45:08 China’s lesson on GDP growth and shareholder returns49:27 Big Booze, GLP-1s and the Lindy effect54:23 Can intangible capital have its own capital cycle59:54 SaaS valuations and the index creation warning signal01:04:10 Why bubbles can help society but hurt investors01:09:09 Why long-term rates may be in a new multi-decade cycle01:14:07 Why Edward Chancellor still sees a role for gold

Brent Kochuba of SpotGamma joins Jack Forehand for the May 2026 OPEX Effect to break down what options positioning is saying after a massive AI and semiconductor-led market rally. They discuss SPX call volume, zero DTE options, dealer gamma, VIX expiration, NVIDIA earnings, oil risk, AI CapEx, and why options flows may help explain both the market’s recent melt-up and the potential for a volatility shift after OPEX.Guest LinksBrent Kochuba on Xhttps://x.com/spotgammaSpotGammahttps://spotgamma.com/Topics CoveredWhy the market has ignored oil shocks and geopolitical risk while AI earnings dominate investor attentionHow AI CapEx, semiconductors and mega-cap tech have driven a powerful melt-up in stocksWhy options volume and zero DTE trading are increasingly important for all investorsHow dealer hedging, delta and gamma can affect stock market movesWhy options expiration can create short-term turning points in markets and volatilityWhat the May OPEX setup says about call-heavy positioning in the S&P 500Why single-stock options activity in NVIDIA, Tesla, Apple, Amazon and AI-related names mattersHow record SPX call volume is being driven by short-dated options flowsWhy Brent is watching VIX expiration, NVIDIA earnings and May 19 to May 20 for volatility expansionWhat oil, VIX, correlation and dispersion are signaling about market riskTimestamps00:00 Intro: SPX call volume, call-heavy positioning and transient options flows00:57 Are we in melt-up mode?05:29 AI, UFOs and how fast market narratives are changing09:00 Why options flows matter more for everyday investors13:39 Could SpaceX become the next huge options market?16:00 How dealer hedging, delta and gamma move through the market20:44 Why OPEX can become a turning point for stocks and volatility23:22 Why May OPEX is so call heavy28:07 The market rally into May expiration33:00 AI rebranding, meme behavior and downside headline risk36:07 Reviewing last month’s oil and volatility setup40:17 How the war flipped market leadership back to tech44:13 Dealer gamma support in the S&P 50049:19 Single-stock gamma in NVIDIA, Tesla, Apple and Amazon51:06 Record SPX call volume and the role of zero DTE54:55 Semiconductor, AI and memory call volume57:50 From bearish positioning to peak-bull dispersion59:22 Oil, the S&P 500 and changing correlations01:03:06 COR1M, dispersion risk and when Brent considers hedging01:04:57 Brent’s key takeaways for May OPEX and volatility expansion

Elena Khoziaeva, Co-Chief Investment Officer and Portfolio Manager at Bridgeway Capital Management, joins Excess Returns to discuss factor investing, small caps, value investing, market concentration, intangibles, passive investing, market neutral strategies, and the role of AI in quantitative investment research.We cover how Bridgeway combines disciplined quantitative models with human judgment, why the S&P 500 may be less diversified than investors think, and how investors can think about diversification when mega-cap growth stocks dominate market returns.Bridgeway Capital Managementhttps://bridgeway.com/I Know What You Did Last Summerhttps://bridgeway.com/perspectives/i-know-what-you-did-last-summer/How Many Stocks Are Effectively in the S&P 500?https://bridgeway.com/perspectives/how-many-stocks-are-effectively-in-the-sp500/Topics CoveredWhy quantitative investing still needs human judgment and skepticismThe difference between smart beta and true multi-factor portfolio constructionHow Bridgeway combines value, quality, sentiment and risk controlsWhy the size premium may depend on how small-cap stocks are definedWhy recently fallen large caps and IPOs can distort small-cap researchHow the small-cap universe has changed as companies stay private longerHow intangible assets affect traditional value and quality metricsWhy value can work in bursts and why timing factor rotations is so difficultHow concentrated the S&P 500 has become using the HHI frameworkWhy passive investing may create opportunities for active small-cap managersHow market neutral strategies can help investors manage equity market volatilityHow AI can help with data, text analysis and trading without replacing investment judgmentTimestamps00:00 Why fewer than 50 stocks are driving S&P 500 returns01:04 Bridgeway’s evidence-based investing approach02:59 Why quantitative models need human judgment07:52 Smart beta vs multi-factor investing11:32 How Bridgeway builds multi-factor portfolios16:08 Rethinking the size premium20:31 Has the small-cap universe gotten worse?23:49 How intangibles change value investing28:05 Does value still work?30:09 Why value returns can be episodic33:11 Why factor investors need patience35:22 How concentrated is the S&P 500?40:29 Factor strategies as portfolio diversifiers41:41 Passive investing and market structure44:27 Managing volatility with market neutral strategies49:40 How systematic managers update their models55:02 How Bridgeway is using AI01:00:03 Elena’s biggest lesson for investors

This episode of our new showThe 100 Year Thinkers brings together Chris Mayer and Ian Cassel for a deep discussion on long-term stock picking, microcap investing, business quality, AI disruption, management teams, and the behavioral skills that separate great investors from great analysts.They explore why the edge in investing may increasingly come from judgment, presence, relationships, patience, and the ability to hold the right businesses through uncertainty.Subscribe to the 100 Year Thinkers on SpotifySubscribe to the 100 Year Thinkers on AppleTopics CoveredWhy being present with management teams may still be an investor edge in the age of AIHow microcap investing differs from small-cap, mid-cap and large-cap investingWhy talking to management can build conviction but also create biasHow Chris Mayer thinks about vertical market software, mission-critical systems and AI disruptionWhy AI may become table stakes rather than a durable competitive advantageHow small companies can use AI to improve workflows, sales, inventory and productivityWhy many microcaps have short shelf lives and rarely become true long-term compoundersThe role of intelligent fanatics, owner-operators and repeat winners in great investmentsWhy management transitions can create powerful microcap opportunitiesThe difference between being a great analyst and being a great investorWhy execution, position sizing, selling losers and holding winners matter more than hit rateHow Matt and Bogumil apply the lessons to AI, business quality and the limits of small business scalabilityTimestamps00:49 Introducing Chris Mayer, Ian Cassel and 100 Year Thinkers04:59 Ian Cassel’s first management meeting and XM Satellite Radio09:00 Why management meetings deepen understanding but can also mislead14:32 Chris Mayer on the real edge in long-term investing18:40 Mission-critical software, systems of record and AI disruption22:45 How microcap companies are using AI in real businesses27:02 AI as table stakes and when disruption creates opportunity31:29 Why most microcaps have short shelf lives35:51 Finding Tom Brady before the market knows he is Tom Brady40:53 Why owner-operators and intelligent fanatics matter45:03 Second-in-command leaders, repeat winners and chips on shoulders49:27 Analyst vs investor and the missing skills of stock picking54:00 Using data to identify investor strengths, weaknesses and decision errors58:14 Position sizing and letting small positions earn the right to grow01:03:00 Peter Lynch, stocks as businesses and learning to think like an owner01:07:00 AI, human judgment and the limits of automation01:11:00 Why not every small business can become the next Facebook01:15:00 Where to follow Bogumil and the 100 Year Thinkers series

This week’s Excess Returns Weekly Wrap examines what Chris Davis and Rich Bernstein can teach investors about letting winners run, inflation risk, market concentration, dividends, AI, and the difference between economic stories and investment returns. Jack Forehand and Matt Zeigler break down clips on portfolio concentration, the 1960s vs. the 1970s, investor complacency, the Fed’s inflation target, durable businesses, and where the next market opportunity may be hiding.Subscribe on SpotifySubscribe on AppleTopics CoveredWhy letting winners run can be so powerful, but so hard for professional investorsChris Davis on how his mother outperformed by never selling great companiesThe tradeoff between concentration, diversification and real-world portfolio riskWhy Rich Bernstein thinks today may look more like the 1960s than the 1970sHow oil prices affect consumer behavior when measured against wagesChris Davis on why perceived risk can be very different from actual riskWhat cars, insurance and investor behavior reveal about market complacencyWhy the Fed’s 2% inflation target may not reflect the world investors are living inThe relationship between valuation, durability and software stocksWhy higher inflation could increase demand for dividends and near-term cash flowChris Davis on why exceptional people and management teams matter in investingWhy AI may be a great economic story but not necessarily a great investment storyTimestamps00:00 Letting winners run, 1960s inflation and investor risk perception02:18 Chris Davis on how his mother outperformed by never selling08:32 Reinvestment risk and the limits of active management12:45 Why oil shocks may matter less when gasoline is low relative to wages20:25 Chris Davis on why feeling safe can make investors take more risk29:20 Rich Bernstein on whether the Fed’s 2% inflation target is outdated34:08 Chris Davis on durability, valuation and software stocks39:39 Why cash flow gives durable companies room to adapt43:16 Rich Bernstein on dividends, inflation and the need for cash today51:55 Chris Davis on why people matter more than investors think56:07 The risk and value of investing with exceptional leaders1:01:30 Rich Bernstein on AI as an economic story vs. an investment story1:05:13 Why AI productivity may not translate into obvious stock market winners

This episode of Last Call breaks down one of the most confusing market environments in recent memory: why stocks continue to rise despite war, oil shocks, and growing macro risks. Through conversations with Jim Paulsen, Ben Hunt, Kevin Muir, and Brent Kochuba, we explore the tension between strong earnings, hidden risks in private credit and global growth, and the powerful role of flows and positioning in driving markets higher.Follow Last Call on SpotifyFollow Last Call on Apple PodcastsTopics CoveredWhy markets are ignoring war, oil shocks, and geopolitical riskThe “supernova” risk in private credit and why it hasn’t hit markets yetHow supply-driven inflation differs from 1970s-style demand inflationWhy pessimistic sentiment may actually be supporting marketsThe role of earnings growth and valuation resets in fueling the rallyBull vs bear case for markets based on macro, earnings, and positioningWhy free cash flow trends may be more concerning than earningsHow options flows and dealer positioning are suppressing volatilityThe AI capex boom and its impact on market leadership and breadthThe growing divide between Mag 7 earnings and the rest of the marketTimestamps00:00 Intro and market overview01:37 Why markets are not falling despite negative news03:00 Buy-the-dip behavior and earnings resilience06:11 Ben Hunt on “supernova” risks in private credit08:00 Hidden credit crunch in middle market companies10:24 Why private credit matters for economic growth14:10 Oil supply shocks and global growth risks17:00 Why markets can ignore risks before they appear18:48 Jim Paulsen on market resilience and sentiment20:00 Why pessimism may reduce downside risk22:24 Inflation vs labor force growth framework24:00 Why current inflation is supply-driven, not demand-driven26:00 Potential shift from inflation focus to growth focus29:11 Kevin Muir on bull vs bear market setup31:00 War impact on rates, oil, and positioning33:00 Fed reaction and shifting rate expectations35:00 Why earnings remain the dominant market driver37:00 Why geopolitics often doesn’t move markets40:00 Bear case: weak free cash flow and employment risk44:26 Brent Kochuba on options flows and positioning47:00 Why markets ignore rising rates and oil49:00 Call buying, dispersion, and tech leadership51:00 Energy as both hedge and AI-driven opportunity54:00 Correlation, volatility, and market structure56:00 Dealer positioning and suppressed volatility58:00 Earnings strength and narrow market leadership01:01:00 Free cash flow vs earnings debate01:01:55 AI capex and long-term market implications

This episode explores one of the most important debates in markets today: whether investors are underestimating the risk of higher inflation and overconcentrating in a narrow group of growth stocks.Richard Bernstein of Janus Henderson Investors joins Excess Returns to explain why today’s environment may look more like the inflationary 1960s than the 1970s, what that means for portfolios, and why many investors may be disappointed with passive index returns over the next decade.Richard walks through the implications of rising import prices, global conflict, and deglobalization, and how these forces could drive a structural shift toward higher inflation and shorter-duration investing. He also explains why market concentration, AI enthusiasm, and capital flows may be setting up a broadening opportunity across overlooked areas of the market.Follow Rich on Twitter:https://twitter.com/RBAdvisorsCompany Website:https://www.rbadvisors.comWhy investors in S&P 500 index funds may face disappointing long-term returnsThe shift from exporting disinflation to importing inflation through global tradeHow war and geopolitical conflict are influencing inflation expectations and marketsWhy today’s environment resembles the 1960s “guns and butter” period more than the 1970sThe case for structurally higher inflation and a potential shift in Fed targetsWhy shorter-duration assets, dividends, and cash flow matter more in inflationary regimesThe risks of overconcentration in AI and mega-cap growth stocksHow capital flows and valuation distortions create opportunities outside the Mag 7The case for international equities and why investors are significantly underweightWhere Bernstein sees the most compelling long-term opportunities across sectors and regions00:00 Intro and why index investors could be disappointed00:01:13 War, inflation, and the impact of rising gasoline prices00:02:40 Importing inflation and the role of global trade dynamics00:03:33 1970s oil shock vs 1960s guns and butter comparison00:05:00 Why today’s inflation environment may be less severe than the 1970s00:06:30 Defense spending, tax cuts, and inflation expectations00:08:54 Why Bernstein is taking the “over” on inflation and deficits00:10:00 The case for a higher long-term inflation target00:11:00 Why the Fed may resist changing its 2% inflation target00:12:00 Deglobalization and the rise of global conflict00:14:00 Global inflation dynamics and divergence across countries00:15:21 Why cash and short-duration assets may outperform00:17:00 Asset-liability mismatches and the endowment model stress00:18:23 Market concentration and parallels to the dot-com bubble00:20:00 AI as an economic story vs an investment story00:21:00 Capital flows, valuation excess, and future return expectations00:22:39 Why market broadening opportunities may emerge00:24:19 Passive flows, ETFs, and market distortions00:25:40 Where Bernstein sees sector opportunities today00:27:34 The case for dividends in an inflationary environment00:31:00 Why near-term cash flow matters more than long-term growth00:33:07 Corporate behavior, capital allocation, and rising hurdle rates00:36:02 Profit cycle strength and why the market should broaden00:41:36 Evaluating IPOs and speculative investments00:47:09 The risk of a lost decade for index investors00:50:21 Gold, commodities, and portfolio diversification00:53:48 Most attractive overlooked opportunities today00:58:06 Biggest long-term risks and what keeps Bernstein up at night